Performance Prediction Model for Urban Dual Carriageway Using Travel Time-Based Indices
Performance prediction based on travel time satisfies both the road users and the traffic managers alike to provide information for smooth traffic flow. The present study aims to develop the performance prediction models for the urban dual carriageway link, using travel time-based indices. Planning...
Gespeichert in:
Veröffentlicht in: | Transportation in developing economies (Online) 2020, Vol.6 (1), Article 2 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | 1 |
container_start_page | |
container_title | Transportation in developing economies (Online) |
container_volume | 6 |
creator | C. P., Muneera Karuppanagounder, Krishnamurthy |
description | Performance prediction based on travel time satisfies both the road users and the traffic managers alike to provide information for smooth traffic flow. The present study aims to develop the performance prediction models for the urban dual carriageway link, using travel time-based indices. Planning time index, congestion index, and travel time index are the indices used in this study for the performance prediction. The geometric data, traffic volume count, and travel time data on the seven dual carriageways located in two urban centers of Kerala form the database for this study. Statistical analyses were carried out for the performance evaluation of urban link using travel time-based indices in each study stretch. The traffic flow in the study stretches was found to vary from 114 to 684 PCU/h/m. Nonlinear regression models were developed and validated for predicting the performance of the urban link by considering the traffic flow rate as an independent variable. Of the different model tried, the exponential model gave accurate prediction on performance with travel time-based indices. A model application was made for performance prediction of dual carriageway with considerable variation in traffic flow rate. The developed model can be used to predict the performance of dual carriageway using travel time parameter. The use of travel time-based performance prediction aids the road users to plan their trip well in advance and further can be used for regional transport planning. |
doi_str_mv | 10.1007/s40890-019-0090-8 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2315544859</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2315544859</sourcerecordid><originalsourceid>FETCH-LOGICAL-c246t-ea72512d916963ea070bba745b69ce4737b3e7c85de184a415d5da8a47fe465b3</originalsourceid><addsrcrecordid>eNp1kMFKAzEQhoMoWGofwFvA82qSTTbJUavWQsUeWjyG2c1s2dLu1qRV-vamrOjJ0wzM9_8DHyHXnN1yxvRdlMxYljFuM8bSYs7IQHBrMyusOv_djb4koxjXjDGhdCLVgLzPMdRd2EJbIZ0H9E21b7qWvnYeNzRd6DKU0NLHA2zoGEJoYIVfcKTL2LQrugjwmbhFs8XsASJ6Om1TBcYrclHDJuLoZw7J8vlpMX7JZm-T6fh-llVCFvsMQQvFhbe8sEWOwDQrS9BSlYWtUOpclznqyiiP3EiQXHnlwYDUNcpClfmQ3PS9u9B9HDDu3bo7hDa9dCLnSklplE0U76kqdDEGrN0uNFsIR8eZOyl0vUKXFLqTQmdSRvSZmNh2heGv-f_QN9Jrcuc</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2315544859</pqid></control><display><type>article</type><title>Performance Prediction Model for Urban Dual Carriageway Using Travel Time-Based Indices</title><source>SpringerLink Journals</source><creator>C. P., Muneera ; Karuppanagounder, Krishnamurthy</creator><creatorcontrib>C. P., Muneera ; Karuppanagounder, Krishnamurthy</creatorcontrib><description>Performance prediction based on travel time satisfies both the road users and the traffic managers alike to provide information for smooth traffic flow. The present study aims to develop the performance prediction models for the urban dual carriageway link, using travel time-based indices. Planning time index, congestion index, and travel time index are the indices used in this study for the performance prediction. The geometric data, traffic volume count, and travel time data on the seven dual carriageways located in two urban centers of Kerala form the database for this study. Statistical analyses were carried out for the performance evaluation of urban link using travel time-based indices in each study stretch. The traffic flow in the study stretches was found to vary from 114 to 684 PCU/h/m. Nonlinear regression models were developed and validated for predicting the performance of the urban link by considering the traffic flow rate as an independent variable. Of the different model tried, the exponential model gave accurate prediction on performance with travel time-based indices. A model application was made for performance prediction of dual carriageway with considerable variation in traffic flow rate. The developed model can be used to predict the performance of dual carriageway using travel time parameter. The use of travel time-based performance prediction aids the road users to plan their trip well in advance and further can be used for regional transport planning.</description><identifier>ISSN: 2199-9287</identifier><identifier>EISSN: 2199-9295</identifier><identifier>DOI: 10.1007/s40890-019-0090-8</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Civil Engineering ; Developing countries ; Development Economics ; Engineering ; Flow velocity ; Independent variables ; Landscape/Regional and Urban Planning ; LDCs ; Original Article ; Performance evaluation ; Performance prediction ; Regional planning ; Regression analysis ; Regression models ; Statistical analysis ; Traffic congestion ; Traffic flow ; Traffic information ; Traffic management ; Traffic models ; Traffic volume ; Transportation ; Transportation planning ; Travel time ; User satisfaction</subject><ispartof>Transportation in developing economies (Online), 2020, Vol.6 (1), Article 2</ispartof><rights>Springer Nature Switzerland AG 2019</rights><rights>Springer Nature Switzerland AG 2019.</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c246t-ea72512d916963ea070bba745b69ce4737b3e7c85de184a415d5da8a47fe465b3</citedby><cites>FETCH-LOGICAL-c246t-ea72512d916963ea070bba745b69ce4737b3e7c85de184a415d5da8a47fe465b3</cites><orcidid>0000-0003-2123-5792</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s40890-019-0090-8$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s40890-019-0090-8$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>C. P., Muneera</creatorcontrib><creatorcontrib>Karuppanagounder, Krishnamurthy</creatorcontrib><title>Performance Prediction Model for Urban Dual Carriageway Using Travel Time-Based Indices</title><title>Transportation in developing economies (Online)</title><addtitle>Transp. in Dev. Econ</addtitle><description>Performance prediction based on travel time satisfies both the road users and the traffic managers alike to provide information for smooth traffic flow. The present study aims to develop the performance prediction models for the urban dual carriageway link, using travel time-based indices. Planning time index, congestion index, and travel time index are the indices used in this study for the performance prediction. The geometric data, traffic volume count, and travel time data on the seven dual carriageways located in two urban centers of Kerala form the database for this study. Statistical analyses were carried out for the performance evaluation of urban link using travel time-based indices in each study stretch. The traffic flow in the study stretches was found to vary from 114 to 684 PCU/h/m. Nonlinear regression models were developed and validated for predicting the performance of the urban link by considering the traffic flow rate as an independent variable. Of the different model tried, the exponential model gave accurate prediction on performance with travel time-based indices. A model application was made for performance prediction of dual carriageway with considerable variation in traffic flow rate. The developed model can be used to predict the performance of dual carriageway using travel time parameter. The use of travel time-based performance prediction aids the road users to plan their trip well in advance and further can be used for regional transport planning.</description><subject>Civil Engineering</subject><subject>Developing countries</subject><subject>Development Economics</subject><subject>Engineering</subject><subject>Flow velocity</subject><subject>Independent variables</subject><subject>Landscape/Regional and Urban Planning</subject><subject>LDCs</subject><subject>Original Article</subject><subject>Performance evaluation</subject><subject>Performance prediction</subject><subject>Regional planning</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Statistical analysis</subject><subject>Traffic congestion</subject><subject>Traffic flow</subject><subject>Traffic information</subject><subject>Traffic management</subject><subject>Traffic models</subject><subject>Traffic volume</subject><subject>Transportation</subject><subject>Transportation planning</subject><subject>Travel time</subject><subject>User satisfaction</subject><issn>2199-9287</issn><issn>2199-9295</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp1kMFKAzEQhoMoWGofwFvA82qSTTbJUavWQsUeWjyG2c1s2dLu1qRV-vamrOjJ0wzM9_8DHyHXnN1yxvRdlMxYljFuM8bSYs7IQHBrMyusOv_djb4koxjXjDGhdCLVgLzPMdRd2EJbIZ0H9E21b7qWvnYeNzRd6DKU0NLHA2zoGEJoYIVfcKTL2LQrugjwmbhFs8XsASJ6Om1TBcYrclHDJuLoZw7J8vlpMX7JZm-T6fh-llVCFvsMQQvFhbe8sEWOwDQrS9BSlYWtUOpclznqyiiP3EiQXHnlwYDUNcpClfmQ3PS9u9B9HDDu3bo7hDa9dCLnSklplE0U76kqdDEGrN0uNFsIR8eZOyl0vUKXFLqTQmdSRvSZmNh2heGv-f_QN9Jrcuc</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>C. P., Muneera</creator><creator>Karuppanagounder, Krishnamurthy</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0003-2123-5792</orcidid></search><sort><creationdate>2020</creationdate><title>Performance Prediction Model for Urban Dual Carriageway Using Travel Time-Based Indices</title><author>C. P., Muneera ; Karuppanagounder, Krishnamurthy</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c246t-ea72512d916963ea070bba745b69ce4737b3e7c85de184a415d5da8a47fe465b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Civil Engineering</topic><topic>Developing countries</topic><topic>Development Economics</topic><topic>Engineering</topic><topic>Flow velocity</topic><topic>Independent variables</topic><topic>Landscape/Regional and Urban Planning</topic><topic>LDCs</topic><topic>Original Article</topic><topic>Performance evaluation</topic><topic>Performance prediction</topic><topic>Regional planning</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Statistical analysis</topic><topic>Traffic congestion</topic><topic>Traffic flow</topic><topic>Traffic information</topic><topic>Traffic management</topic><topic>Traffic models</topic><topic>Traffic volume</topic><topic>Transportation</topic><topic>Transportation planning</topic><topic>Travel time</topic><topic>User satisfaction</topic><toplevel>online_resources</toplevel><creatorcontrib>C. P., Muneera</creatorcontrib><creatorcontrib>Karuppanagounder, Krishnamurthy</creatorcontrib><collection>CrossRef</collection><jtitle>Transportation in developing economies (Online)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>C. P., Muneera</au><au>Karuppanagounder, Krishnamurthy</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Performance Prediction Model for Urban Dual Carriageway Using Travel Time-Based Indices</atitle><jtitle>Transportation in developing economies (Online)</jtitle><stitle>Transp. in Dev. Econ</stitle><date>2020</date><risdate>2020</risdate><volume>6</volume><issue>1</issue><artnum>2</artnum><issn>2199-9287</issn><eissn>2199-9295</eissn><abstract>Performance prediction based on travel time satisfies both the road users and the traffic managers alike to provide information for smooth traffic flow. The present study aims to develop the performance prediction models for the urban dual carriageway link, using travel time-based indices. Planning time index, congestion index, and travel time index are the indices used in this study for the performance prediction. The geometric data, traffic volume count, and travel time data on the seven dual carriageways located in two urban centers of Kerala form the database for this study. Statistical analyses were carried out for the performance evaluation of urban link using travel time-based indices in each study stretch. The traffic flow in the study stretches was found to vary from 114 to 684 PCU/h/m. Nonlinear regression models were developed and validated for predicting the performance of the urban link by considering the traffic flow rate as an independent variable. Of the different model tried, the exponential model gave accurate prediction on performance with travel time-based indices. A model application was made for performance prediction of dual carriageway with considerable variation in traffic flow rate. The developed model can be used to predict the performance of dual carriageway using travel time parameter. The use of travel time-based performance prediction aids the road users to plan their trip well in advance and further can be used for regional transport planning.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s40890-019-0090-8</doi><orcidid>https://orcid.org/0000-0003-2123-5792</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2199-9287 |
ispartof | Transportation in developing economies (Online), 2020, Vol.6 (1), Article 2 |
issn | 2199-9287 2199-9295 |
language | eng |
recordid | cdi_proquest_journals_2315544859 |
source | SpringerLink Journals |
subjects | Civil Engineering Developing countries Development Economics Engineering Flow velocity Independent variables Landscape/Regional and Urban Planning LDCs Original Article Performance evaluation Performance prediction Regional planning Regression analysis Regression models Statistical analysis Traffic congestion Traffic flow Traffic information Traffic management Traffic models Traffic volume Transportation Transportation planning Travel time User satisfaction |
title | Performance Prediction Model for Urban Dual Carriageway Using Travel Time-Based Indices |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-31T08%3A12%3A29IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Performance%20Prediction%20Model%20for%20Urban%20Dual%20Carriageway%20Using%20Travel%20Time-Based%20Indices&rft.jtitle=Transportation%20in%20developing%20economies%20(Online)&rft.au=C.%20P.,%20Muneera&rft.date=2020&rft.volume=6&rft.issue=1&rft.artnum=2&rft.issn=2199-9287&rft.eissn=2199-9295&rft_id=info:doi/10.1007/s40890-019-0090-8&rft_dat=%3Cproquest_cross%3E2315544859%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2315544859&rft_id=info:pmid/&rfr_iscdi=true |